Noor Mohamed, Mohamed Husain2023-07-222023-07-222023-07-21vt_gsexam:38222http://hdl.handle.net/10919/115819Scaling up application performance on single high-end machines is increasingly becoming difficult due to scalability challenges of processor interconnects, cache coherence protocols, and memory bandwidth. Significant prior work has addressed this problem by scaling-out application threads across multiple nodes to exploit resources outside the single machine boundary. Prior works have also leveraged heterogeneous instruction set architecture (ISA) systems to improve application performance as well as energy-efficiency, a major cost driver in datacenters, by augmenting high-end servers with power-efficient embedded boards. Existing works, however, suffer from deployability challenges due to dependencies on the operating system or programming models that require non-trivial application modifications. We introduce CRIU-RTX, a userspace framework to scale-out multi-threaded applications across multiple nodes. Integrated with HetMigrate, a prior work on migrating processes across heterogeneous-ISA systems, CRIU-RTX can suspend a subset of threads in a process and resume their execution on different nodes, including, but not limited to heterogeneous-ISA nodes. CRIU-RTX implements distributed shared memory in userspace, thereby allowing application threads to access distributed memory transparently without any operating system dependency. Our experimental evaluations show 21% to 43% performance gains while scaling-out applications across x86-64 servers, and energy efficiency gains of up to 18% while scaling-out across a cluster of x86-64 server and ARM64 embedded boards. Since CRIU-RTX does not depend on operating system modifications, it can be easily deployed on a diverse set of machines, including, but not limited to ISA-different machines running the stock Linux operating system.ETDenIn CopyrightHeterogeneous SystemsDistributed ExecutionEnergy EfficiencyThesis